The Future of RAG: Exploring Advanced LLM Architectures with LangChain and Redis

Simplify RAG development for AI apps with LangChain and Redis.

Watch this session for an in-depth exploration of Retrieval-Augmented Generation (RAG) and its application within the LangChain framework. RAG is a key technique for integrating domain-specific data with Large Language Models (LLMs) that is crucial for organizations looking to unlock the power of LLMs. 

This session will highlight LangChain’s role in facilitating RAG-based applications, advanced techniques, and the critical role of Redis Enterprise in enhancing these systems’ adaptability, resiliency, and performance at scale.

Watch this session to gain insight into:

• The purpose and value of RAG
• The evolution of RAG systems from basic to modern techniques that can handle diverse data types and business needs
• Practical examples illustrating the power of LangChain and Redis in RAG architectures

Event Speakers

Tyler Hutcherson

Senior Applied AI Engineer
Redis

Lance Martin

Software Engineer
LangChain

Nuno Campos

Founding Engineer
LangChain